An Activity Recognition Algorithm Based on Energy Expenditure Model
Yuhuang Zheng · Advances in computer science research · 2015
Human activity recognition via triaxial accelerometers can provide valuable information to evaluate functional abilities.In this paper, we present an accelerometer sensor-based approach for human activity recognition.Our proposed recognition method uses a model of Activity Energy Expenditure to recognize six activities.The classifier utilizes Fast Fourier transform (FFT) and Discrete Wavelet Transform (DWT) algorithms to get energy expenditures of different activities.Every activity is recognized by the max amplitude and its frequency, 1-D decomposition energy of triaxial accelerometer signals.This activity recognition method can recognize six activities with an average accuracy of 90% using only a single triaxial.